Initial project feasibility study


To do

  •            Information Gathering 
  •            System States Descriptions 
  •            Possible Decitions 
  •            Quality Measure 
  •            Rewards/ Expected Performance 

Findings 

Project title: Investigating improving the drill ship's mining rate with an autonomous mining path predicting Machine Learning Model.


Project description: using the historic and current mining time series data and environmental parameters to create a Machine learning model than will perform a few days/ a week's mining rate performance forecast.


Key areas:

-Mining Rate = Area covered 
                      Time

-Overlaps   
            
when mining, only 60 to 70% overlap is preferred for material extraction  


-RPM (Revolutions Per Minute) How fast the drill tool is rotating 

Preliminary mining parameters to consider:

Depth penetration
Torque
Weight on bit 
Vessel movement efficiency
3D data
Hydrophone data
Weather prediction

Geology 
    lithology 

Direction 
    North, South, Inshore, and Offshore 

Notes:

  • Quick drill tool lift up is 8 meters and drop for eight meters 
  • Vessel movement efficiency should be considered.
  • Considered Pre-move data 
  • Environmental factors 
Next:
Draft Gantt Chart 
Get Supervisor Approval

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